Failed to deploy the model (715-123420: Our system has detected this request as unusual activity for your account. If you are confident this is in error, please contact support.)

Hello Adhy Dharma Fiadimas Nitiwidigdho,

Greetings! Thanks for raising this question in the Q&A forum.

Error 715-123420 is generated by Azure's Real-Time Fraud Protection (RTFP) system, not by a problem with your deployment configuration. It blocks new model deployments at the platform level before the request reaches provisioning, which is why it fails immediately regardless of which model or region you try. There is no config change, region switch, or retry on your side that will clear this. It has to be manually reviewed and released by Microsoft's internal Fraud Protection and Security team.

Here is how to get it resolved:

Avoid deleting and recreating the resource or resource group. Repeating that pattern will not clear the flag and can make the activity look more suspicious rather than less.

Open a support request through the Azure portal. Go to Help + support > Create a support request. You do not need a paid support plan for this, since fraud and account-protection reviews are handled as a subscription or billing matter, not as a technical support ticket. Choose Subscription management or Billing as the issue type if Technical support is not available on your plan.

State the issue clearly in the request. Mention that you are hitting error 715-123420 on a model deployment (gpt-5.2) in Microsoft Foundry, and that this is a Real-Time Fraud Protection (RTFP) block requiring review by the internal Fraud Protection and Security team, not standard troubleshooting.

Include full diagnostic details. Provide your subscription ID, tenant ID, the resource group and resource name where the deployment was attempted, the exact model and deployment type (gpt-5.2), the UTC timestamp of a failed attempt, and any correlation ID or request ID shown in the error details or Activity log for that deployment. To find the correlation ID, go to the resource group, open Activity log, locate the failed deployment operation, and open its error details.

If this answer helps you kindly accept the answer which will help others who have similar questions.

Best Regards,

Jerald Felix.

Hello @Adhy Dharma Fiadimas Nitiwidigdho ,

Welcome to Microsoft Q&A .Thank you for reaching out to us.

The current behavior suggests that the deployment request may be failing during an earlier validation stage before the model provisioning process begins. The error message itself does not expose the exact validation reason, so confirmation requires additional backend investigation.

Possible areas that may require review include:

• Subscription eligibility validation
• Subscription-level authorization checks
• Automated risk or trust validation controls
• Model deployment access validation

Regarding the request for an RTFP review, the available information does not conclusively confirm that an RTFP restriction is present. However, the observed pattern is consistent with scenarios where additional backend validation may be required to determine whether a subscription-level condition is preventing deployments from completing.

The following checks can help rule out common deployment blockers before backend investigation.

1. Confirming Model Availability Verify that the selected models are supported in the intended region and deployment type. Checks:
   • Confirm model availability for the selected Azure region.
   • Confirm that the selected deployment type (for example, Global Standard) is supported for the model.
2. Validating Quota and Capacity Availability Confirm that sufficient quota is available for:
   • Subscription
   • Region
   • Selected model deployment
   Quota or capacity issues normally return more specific quota-related messages. However, validating quota helps eliminate standard deployment limitations.
3. Verifying Resource Provider Registration Confirm that the required resource providers are registered and in a healthy state:
   • Microsoft.CognitiveServices
   • Microsoft.MachineLearningServices
   Expected status: Registered
4. Reviewing Governance and Policy Restrictions Review Azure Policy assignments that may restrict:
   • AI model deployments
   • Allowed regions
   • Resource types
   • Deployment configurations
5. Performing Additional Deployment Validation To determine whether the issue is limited to a specific deployment method or occurs at the service level:
   • Retry after a short interval to rule out temporary service behavior.
   • Attempt a deployment with a new deployment name to exclude deployment-specific inconsistencies.
   • Test deployment through Azure AI Foundry portal.
   • If possible, test through Azure CLI or ARM/Bicep to confirm whether the failure occurs at the service layer.

As an additional verification , please note that

For sponsored subscriptions, it may also be useful to confirm that the selected models appear under the appropriate model collection in Azure AI Foundry, as model eligibility and billing behavior can vary depending on the model source.

The following references might be helpful , please check them out

• Region availability for Foundry Models sold by Azure - Microsoft Foundry | Microsoft Learn
• Azure OpenAI in Microsoft Foundry Models Quotas and Limits - Microsoft Foundry | Microsoft Learn
• Azure resource providers and types - Azure Resource Manager | Microsoft Learn
• Overview of Azure Policy - Azure Policy | Microsoft Learn
• az cognitiveservices account deployment | Microsoft Learn
• Sponsorship Coverage for Microsoft Foundry Models | Microsoft Learn

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Thank you